Measurement and signature intelligence analysis and reduction technique

Abstract

Methods and apparatus compress data, comprising an In-phase (I) component and a Quadrature (Q) component. The compressed data may be saved into a memory or may be transmitted to a remote location for subsequent processing or storage. Statistical characteristics of the data are utilized to convert the data into a form that requires a reduced number of bits in accordance with the statistical characteristics. The data may be further compressed by transforming the data, as with a discrete cosine transform, and by modifying the transformed data in accordance with a quantization conversion table that is selected using a data type associated with the data. Additionally, a degree of redundancy may be removed from the processed data with an encoder. Subsequent processing of the compressed data may decompress the compressed data in order to approximate the original data by reversing the process for compressing the data with corresponding inverse operations.

Description

[0001] This application is a continuation of common-owned, co-pending U.S. application Ser. No. 09 / 269,818 filed on Oct. 11, 2002, naming Francis Robert Cirillo and Paul Leonard Poehler as inventors and claiming priority to provisional U.S. application Ser. No. 60 / 392,316 (“Measurement and Signature Intelligence Analysis and Reduction Technique”), filed Jun. 28, 2002.FIELD OF THE INVENTION [0002] The present invention relates to compressing and decompressing data such as synthetic aperture radar data. BACKGROUND OF THE INVENTION [0003] Compression of Synthetic Aperture Radar (SAR) data may require that both magnitude and phase information be preserved. FIG. 1 shows data processing of synthetic aperture radar data according to prior art. Synthetic aperture radar data 102 are typically collected in analog format by an antenna 101 and is converted to digital format through an Analog-to-Digital (A / D) converter 103. The raw, unprocessed data are referred to as Video Phase History (VPH) d...

AI Technical Summary

Benefits of technology

[0008] The present invention provides methods and apparatus for compressing data comprising an In-phase (I) component and a Quadrature (Q) component. The compressed data may be saved into a memory or may be transmitted to a remote location for subsequent processing or storage. Statistical characteristics of the data are utilized to convert the data into a form that requires a reduced number of bits in accordance with its statistical characteristics. The data may be further compressed by transforming the data, as with a discrete cosine transform, and by modifying the transformed data in accordance with a quantization conversion table that is selected using a data type associated with the data. Additionally, a degree of redundancy may be removed from the processed data with an encoder. Subsequent processing of the compressed data may decompress the compressed data in order to approximate the original data by reversing the process for compressing the data with corresponding inverse operations.

[0009] In a first embodiment of the invention, data are compressed with an apparatus comprising a preprocessor, a transform module, a quantizer, an encoder, and a post-processor. The preprocessor separates the data into an I component and a Q component and bins each component according to statistical characteristics of the data. The transform module transforms the processed data into a discrete cosine transform that is quantized by the quantizer using a selected quantization conversion table. The encoder partially removes redundancy from the output of the quantizer using Huffman coding. The resulting data can be formatted by a post-processor for storage or transmittal. With a second embodiment, the preprocessor converts the I and Q components into amplitude and phase components and forms converted I and Q components.

Problems solved by technology

Existing complex SAR sensors collect increasingly large amounts of data.

However, sensors are typically associated with on-board processors that have limited processing and storage capabilities.

However, while such compression algorithms generally work quite well for magnitude imagery, the compression algorithms may not efficiently compress phase information.

With SAR data 102, compression algorithms typically do not achieve compression ratios of more than ten to one without significant degradation of the phase information.

Existing optical algorithms are inadequate for compressing complex multi-dimensional data, such as SAR data compression.

However, such characteristics may not be applicable to complex multi-dimensional data.

Furthermore, the quality of the processed complex multi-dimensional data is not typically visually assessable.

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